saliency
vision_transformer_tf
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| saliency | vision_transformer_tf | |
|---|---|---|
| 4 | 4 | |
| 929 | 24 | |
| 0.8% | - | |
| 3.6 | 10.0 | |
| about 1 month ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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saliency
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[D] Is the math in Integrated gradients (4K citations) wrong?
Found relevant code at https://github.com/PAIR-code/saliency + all code implementations here
- How to display which parts of a single image a Keras model found to be the most significant when making a prediction?
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Gradients of model output layer and intermediate layer wrt inputs
I’m trying to visualize model layer outputs using the saliency core package package on a simple conv net. This requires me to compute the gradients of the model output layer and intermediate convolutional layer output w.r.t the input. I’ve attempted to do this in the last code block, but I run into the error
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A Visual History of Interpretation for Image Recognition
[2]: https://github.com/PAIR-code/saliency
vision_transformer_tf
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Implemented Vision Transformers from scratch using TensorFlow 2. x 🚀, Finetuning and Converting to TF-Lite ✅
Hi r/learnmachinelearning, I am done implementing the paper AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE, popularly known as the Vision Transformer paper. Using my implementation any vision transformer model can be finetuned pretty easily with any custom dataset, Converting weights to TensorFlow Lite is also supported. My codebase is also very straightforward to understand and debug. One can learn how the vision transformer works internally by debugging the whole pipeline. Link to the GitHub Project: https://github.com/TheTensorDude/vision_transformer_tf
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[P] Finetune any Vision Transformer architecture on your custom data 🚀, Convert to TensorFlow Lite ✅
The GitHub link to the project can be found here.
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[P] Implemented Vision Transformers 🚀 from scratch using TensorFlow 2.x
My implementation: GitHub Link
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Implemented Vision Transformers 🚀 from scratch using TensorFlow 2.x
My implementation: https://github.com/TheTensorDude/vision_transformer_tf
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